Big Data Analytics and Predictive Modeling Approaches for the Energy Sector

Abstract

This paper describes recent results achieved in the analysis of geo-distributed sensor data generated in the context of the energy sector. The approaches described have roots in the Big Data Analytics and Predictive Modeling research fields and are based on distributed architectures. They tackle the energy forecasting task for a network of energy production plants, by also taking into consideration the detection and treatment of anomalies in the data. This research is motivated by and consistent with the objectives of research projects funded by the European Commission and by many national governments.